Nearest cluster center decision in hierarchical classification process

Khalifa Djemal 1 Hichem Maaref 1
1 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes
Abstract : The hierarchical classification method based on SVM multi learning process has proved its abilities to classify large databases. However, some misclassification can be detected through the hierarchy levels. To minimize these errors and improving the rate of classification, we propose to use Nearest Cluster centers (NCC) in the hierarchy structure to correct the classification ambiguities. Obtained results on IRIS database prove the given improvement of global classification rate.
Keywords : Hierarchical classification multi-learning NCC SVM
Document type :
Conference papers
Complete list of metadatas
https://hal.archives-ouvertes.fr/hal-01777619
Contributor : Frédéric Davesne <>
Submitted on : Tuesday, April 24, 2018 - 11:37:41 PM
Last modification on : Monday, October 28, 2019 - 10:50:22 AM

Identifiers

Collections

UNIV-EVRY | IBISC | IBISC-SIBI

Citation

Khalifa Djemal, Hichem Maaref. Nearest cluster center decision in hierarchical classification process. 2014 Information and Communication Technologies Innovation and Application (ICTIA 2014), Mar 2014, Sousse, Tunisia. ⟨10.1109/ICTIA.2014.7883767⟩. ⟨hal-01777619⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

61

Contact

Informations

CCSD